Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/idempotent/non-destructive, and the description adds real behavioral context: it returns verbatim creator text, credit, source, and model, and it explicitly disclaims performance claims, framing adaptation notes as factual guidance only. That epistemic boundary is valuable and not derivable from annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action and return contents, followed by the adaptation caveat. The closing disclaimer is slightly long but it carries substantive semantic content, so it earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description fully enumerates what is returned (exact prompt text, creator credit and source, source model, adaptation notes) and explains adaptation behavior. Combined with annotations covering safety, an agent has everything needed to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description goes further by clarifying what 'model' does — it triggers factual adaptation notes about other Atlas shots and current supported price when the target differs. That adds meaning beyond the schema's terse 'Target model family'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Get the full, sourced prompt that best matches a shot') and names the distinguishing attribute (sourced, exact creator text). It is clearly separable from find_shot, which locates shots rather than returning prompt content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explains accepted inputs (free text or a slug from find_shot) and the optional target-model case, which implies the find_shot → best_prompt workflow. It does not explicitly say when to prefer this over fix_prompt or refine_shot, so exclusions are absent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.